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针对小型电子感应加速器中的剂量控制问题，提出一种自适应最大剂量搜索与稳定控制方法。该算法通过动态调节电子枪注入时序与辅助俘获时序，实现两者最优相位匹配，以优化剂量率。算法采用两级优化：先通过粗搜索快速锁定最优时序区间，随后利用自适应梯度上升算法进行局部精细寻优，以提高收敛速度与精度；同时引入稳定控制机制，实时修正由热漂移及运行扰动引起的剂量率衰减。实验结果表明：与传统网格搜索算法相比，所提方法达到最大剂量率的时间缩短80%；在长时间运行过程中，算法的剂量率波动幅度低于14.7%，较传统方法下降了14.9%。该方法实现了加速器输出X射线剂量的快速搜索与稳定控制，可为便携式及其他电子加速器在线参数优化控制提供方案。
Abstract：In allusion to the dose⁃control problem of small⁃size Betatron, an adaptive maximum⁃dose search and stabilization control method is proposed. In this algorithm, the electron⁃gun injection timing and the auxiliary⁃capture timing are adjusted dynamically to realize the optimal phase matching between the two, thereby optimizing the dose rate. A two⁃stage optimization strategy is adopted at this algorithm: a coarse search is used to rapidly lock the optimal timing interval, and then an adaptive gradient⁃ascent algorithm is used to conduct the local fine⁃optimization, so as to improve convergence speed and accuracy. A stabilization control mechanism is also introduced to compensate in real time for dose rate decay caused by thermal drift and operational disturbances. The experimental results show that, in comparison with conventional grid⁃search algorithm, the time to reach the maximum dose rate is shorten by 80%. During prolonged operation, the fluctuation range of the algorithm’s dose rate is less than 14.7% and is decreased by 14.9% compared with traditional method. The proposed method can realize rapid search and stable control of the accelerator’s X⁃ray output and provide a practical scheme for online parameter optimization and control of portable and other electron accelerators.
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基本信息:
DOI：10.16652/j.issn.1004⁃373x.2026.08.003
引用信息:
[1]宋博翰1,2,刘琦1,王仁波1,2,等.基于自适应算法的小型感应加速器剂量最优保持方法研究[J],2026,49(8):14⁃19.DOI:10.16652/j.issn.1004⁃373x.2026.08.003.
基金信息:
江西省主要学科学术带头人培养计划项目（20243BCE51132）;江西省自然科学基金项目（20252BAC200169）